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Investigating the effects of a
high carbohydrate, high fat diet
on the ghrelin-serotonin 2C
receptor pathway in the brain
Kara Stuart
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Acknowledgements
I would like to acknowledge and thank the USQ Functional Food Group for their
friendship and laboratory assistance. Thank you to Anna Balzer, Ryan Du Preez,
Stephen Wanyoni and Oliver John for rat tissue samples and assistance with tissue
collection. To the USQ research and Innovation and Centre for Health Sciences
Research, thank you for funding this project. Thank you to my supervisors Dr Eliza
Whiteside and Dr Sunil Panchal for their training and support. Thank you to Joanna
Turner for exceeding in her role as Honour Co-ordinator.
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Table of Contents
CHAPTER 1 ........................................................................................... 10
INTRODUCTION .................................................................................... 10
Obesity ................................................................................................ 10
The Ghrelin Axis .................................................................................... 11
Ghrelin .............................................................................................. 11
Ghrelin O-acyltransferase (GOAT) ......................................................... 14
Serotonin 2C Receptor (5-HT2CR) ............................................................... 15
Serotonin agonists in the treatment of obesity ....................................... 16
Expression of 5-HT2CR in the brain in response to diet ............................. 17
Link between ghrelin axis and serotonergic pathway ............................... 18
The Gut Microbiome............................................................................... 20
Short Chain Fatty Acids ....................................................................... 22
The role of butyrate in intestinal health and epigenetics .......................... 22
Hypotheses .......................................................................................... 26
Aims and objectives ............................................................................... 26
CHAPTER 2 ........................................................................................... 27
EXPERIMENTAL PROCEDURES ................................................................. 27
Tissue collection ................................................................................. 27
Protein extraction ............................................................................... 27
mRNA extraction ................................................................................ 28
cDNA synthesis .................................................................................. 29
Analysis of gene expression by real-time quantitative polymerase chain
reaction ............................................................................................. 29
Western Blot (Immunoblots) ................................................................ 30
Co-culture of colon microbiome with human colon cancer cells (SW620) .... 31
Epigenetic Chromatin Modification Enzyme Plate .................................... 33
CHAPTER 3 ........................................................................................... 34
RESULTS .............................................................................................. 34
Messenger RNA (mRNA) expression analysis by RT-PCR .......................... 34
Western (Immunoblot) Analysis of 5-HT2CR protein expression ................. 37
Epigenetic chromatin modification enzyme H384 plate ............................ 38
CHAPTER 4 ........................................................................................... 39
DISCUSSION ........................................................................................ 39
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Conclusion ......................................................................................... 44
REFERENCES ........................................................................................ 46
APPENDIX ............................................................................................ 54
Appendix A ........................................................................................ 54
Modified corn starch and high carbohydrate, high fat diet break-down ...... 54
Appendix B ........................................................................................ 55
Gifu anaerobe media (GAM) preparation and rat colon content culture ...... 55
SW620 and colon content culture preparation ........................................ 55
Tissue collection and sample homogenisation ......................................... 56
Appendix C ........................................................................................ 57
Animal weights ................................................................................... 57
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Abbreviations
5-HT - 5-hydroxytryptamine, serotonin
5-HT2CR - serotonin 2C receptor
AG - acylated ghrelin
AgRP - agouti related peptide
AOM – Azoxymethane
ARC – arcuate nucleus
BCA – bicinchonic acid
BMI - body mass index
CS – corn starch
CTR – control
CTRW - control plus tryptophan
DIO – diet-induced obesity
DMEM - Dulbecco's Modified Eagle's Mdium
DSS – dextran sodium/sulfate
DZIP3 – Deleted in azoospermia (DAZ) interacting zinc finger protein 3
ECL – enhanced chemiluminescent
ER- α – oestrogen receptor α
GAM – gifu anaerobe media
GHRL – ghrelin
GHSR - Growth hormone secretagogue receptor
GIT - Gastrointestinal tract
GOAT - Ghrelin-O-acyltransferase
H8C8 – HCHF eight weeks, CS eight weeks
HCHF - High carbohydrate and high fat diet
HDACi – histone deactylase inhibitor
HED – high energy diet
HEDW – high energy plus tryptophan
HGC – high gene count
HPA – hypothalamic-pituitary-adrenal
Hprt1- Hypoxanthine phosphoribosyltransferase 1
HRP – horseradish peroxidase
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KAT5 - Lysine acetyltransferase 5
KAT6A - Lysine acetyltransferase 6A
LGC – low gene count
mCPP – (m-chlorophenylpiperazine)
MUC2 – mucin 2
MYSM1 - Myb Like, SWIRM And MPN Domains 1
NCOA6 - Nuclear receptor coactivator 6
NEK6 - NIMA related kinase 6
NPY – neuropeptide Y
NSPs – non-starch polysaccharides
OF – oligofructose
PAK1 - P21 (RAC1) activated kinase 1
PBS – phosphate buffered saline
POMC – proopiomelanocortin
PRMT 1, 2, 5, 7- Protein arginine methyltransferase 1, 2, 5, 7
RIPA – radioimmunoprecipitation assay
RPLP0 - Ribosomal protein lateral stalk subunit P0
RS – resistant starch
SCFA – short chain fatty acid
SUV420H1 - Histone-lysine N-methyltransferase
TBST – tris-buffered saline with Tween 20
Tlr4 – Toll like receptor 4
Tph1 - Tryptophan hydroxylase 1
UAG – unacylated ghrelin
UBE2A - Ubiquitin conjugating enzyme E2 A
VTA – ventral tegmental area
WL – weight loss
α -MSH - α -melanocyte stimulating hormone
βME- β-mercapto-ethanol
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Abstract
Obesity is a global pandemic with more than 13% of the adult population classified
as obese and 39% overweight. Strategies to treat and prevent the energy
imbalance that causes obesity could be developed by understanding the gene
expression and epigenetic changes that drive appetite and energy regulation.
Ghrelin is a stomach and brain-secreted peptide hormone that stimulates appetite
and energy balance. It is activated by the enzyme ghrelin-O-acyltransferase
(GOAT) and is mediated by the ghrelin receptor (GHSR1a). Serotonin (5-HT) is
another stomach-secreted hormone that regulates appetite by stimulating post-
meal satiety and reducing food intake through binding to the 2C serotonin receptor
(5-HT2CR) in the brain. Plasma ghrelin levels are increased and plasma 5-HT levels
are decreased by a high fat diet in rats, however the expression of ghrelin, GOAT,
GHSR1a and 5-HT2CR by the brain in response to a long term high carbohydrate
and high fat diet (HCHF), representative of the ‘Western’ diet, has not been
explored. This study investigated the effects of diet and diet composition change
(reverting from a HCHF diet back to a standard corn starch (CS) diet) on the
expression of the ghrelin and 5-HT2CR pathways in the rat brain using real time
reverse transcriptase polymerase chain reaction (RT-PCR) and Western Blot
(Immunoblot). This study also investigated whether the HCHF diet could influence
the epigenome of human colon cells via changes in the gut microbiome. There was
not a consistent upregulation or down-regulation of ghrelin, GOAT or GHSR in
response to the HCHF diet however there was a consistent and significant decrease
in the expression of both GOAT and GHSR when the diet was reverted back to the
standard diet. The expression of 5-HT2CR was more consistent with all rats fed the
HCHF diet demonstrating a non-significant decrease in the expression of the 5-
HT2CR and three out of four rats demonstrating a non-significant increase in
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response to reverting back to the standard diet. In order to investigate the effects
of the HCHF-induced microbiome population change on colon cells (independent
of other diet-induced changes), colon contents from rats fed the HCHF and CS
were cultured under anaerobic conditions and then in vitro co-cultured with human
colon cells. RT-PCR analysis of the expression of epigenetic modifying enzymes in
both groups demonstrated a twelve-fold increase in the expression of deleted in
azoospermia (DAZ) interacting zinc finger protein 3 (DZIP3) in response to the
HCHF. DZIP3 is a chromatin modifying enzyme and thus may influence changes
to the epigenome. In summary, these findings support a role for brain-expressed
GOAT and GHSR1a in reducing the ability of ghrelin to stimulate appetite and for
brain-expressed 5-HT2CR to induce satiety in the brain when HCHF food is
removed. This study also provides pilot data that HCHF can modify the epigenome
of colon cells via changes in the gut microbiome.
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CHAPTER 1
INTRODUCTION
Obesity
As of 2014, there were more than 1.9 billion overweight and 600 million obese
adults worldwide, translating to 39% of the adult population being overweight and
13% obese (World Health Organisation 2015). The obesity ‘pandemic’ has been
attributed to factors such as a sedentary lifestyle, insufficient physical activity, the
Western diet and genetics (Le Chatelier et al. 2013). Diet is an important
modifiable factor especially when considering energy intake versus energy
expenditure. Appetite, or the motivation to eat, is also an integral factor in obesity.
The ghrelin axis is a short term regulator of appetite and satiety and it appears
that this pathway is dysregulated in obese individuals, with obese individuals
having paradoxically low levels of ghrelin. Emerging evidence suggests that
serotonin (5-HT), acting via the serotonin 2C receptor (5-HT2CR), induces satiety
and thus is also a key regulator of appetite. Whether this pathway is still intact in
obese individuals has not been explored. The link between diet, obesity and the
ghrelin and serotonergic pathways in the brain has not yet been reported.
Additionally, obese individuals exhibit characteristic changes in their gut
microbiome, with overall less bacterial diversity and disrupted ratio of the two
dominant bacterial phyla, Bacteroides and Firmicutes (Mishra et al. 2016). Obese
humans and rats characteristically have increased numbers of Firmicutes and
lowered numbers of Bacteroides in comparison to healthy weight individuals.
These differences can lead to epigenetic changes in the colon that can also
influence gut and overall health.
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The Ghrelin Axis
Ghrelin
Ghrelin is an orexigenic peptide hormone that stimulates appetite by transmitting
a ‘hunger signal’ to the brain (Mishra et al. 2016). Ghrelin has a significant role in
regulating food intake and energy balance, therefore changes in the expression of
ghrelin and other factors regulating the ghrelin axis may contribute to the
development of obesity. Ghrelin levels increase with body mass index (BMI),
however obese individuals exhibit paradoxically low levels of ghrelin. Ghrelin is
activated by the enzyme ghrelin O-acyltransferase (GOAT) and functions via
binding to the growth hormone secretagogue receptor (GHSR). GOAT also
increases with BMI, but unlike ghrelin, circulating levels of GOAT are also
increased in obesity (Goebel-Stengel et al. 2013).
Ghrelin was initially discovered in the gastrointestinal tract (GIT) and is most well-
known for its involvement in the regulation of energy metabolism and stimulation
of growth hormone (Kojima et al. 1999). However, ghrelin has many additional
physiological functions, making it more than simply a growth hormone stimulating
peptide, as indicated by its widespread expression throughout the body including
a sup-population of cells in the hypothalamus (Watterson et al. 2012). Ghrelin
functions in metabolism, appetite regulation and gut motility, and is also involved
in the function of the immune, cardiovascular and reproductive systems (Kojima
& Kangawa 2010).
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There are multiple steps involved in the production of ghrelin. After cleavage from
preproghrelin, the enzyme GOAT facilitates the addition of an octanoyl group to
the hydroxyl group of the serine residue, forming acylated ghrelin (AG) (Figure 1)
(Gutierrez et al. 2008; Khatib et al. 2015).
Figure 1: A schematic diagram of the ghrelin axis illustrating the process in which
acylated ghrelin (AG) is synthesised. Unacylated ghrelin (UAG) is cleaved from its
precursor, preproghrelin. Ghrelin-O-acyltransferase (GOAT) facilitates the addition of an
octanoyl group to unacylated ghrelin to form AG. AG is able to bind to the ghrelin
secretagogue receptor 1a (GHSR1a), while it is hypothesised that UAG binds to an
unknown receptor.
It is only the acylated form of ghrelin which can bind to, and activate its receptor,
the GHSR, specifically via the 1a subunit (GHSR1a) (Kojima et al. 1999). Results
regarding the role of unacylated ghrelin (UAG) have been inconsistent. It was
thought that due to its inability to bind to GHSR1a, UAG may not have any
biological function, however a study by Toshinai and colleagues (2006) found that
UAG facilitates biological effects similar to AG. The central administration of UAG
to Wistar rats increased feeding through the activation of the orexin pathway in
the hypothalamus. Interestingly, central administration of UAG to rats lacking
GHSR still induced an orexigenic response, indicating that UAG binds to a currently
unknown receptor to produce its biological actions. A more recent study by
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Fernandez et al. (2016), reported that UAG acts on a subset of neurons in arcuate
nucleus (ARC) in the hypothalamus (a region known for its involvement in appetite
regulation) through a GHSR-independent pathway. The study found that centrally
administered UAG impaired the action of peripherally administered AG, at least in
part by activation of proopiomelanocortin (POMC) neurons, having an antagonistic
effect on AG (Fernandez et al. 2016). AG makes up only a small proportion of
circulating ghrelin, with UAG contributing to approximately 80-90% of circulating
total ghrelin (Pacifico et al. 2009). This is possibly due to the shorter half-life of
AG (Toshinai et al. 2006; Fernandez et al. 2016). Changes in the ratio of
circulating forms of ghrelin, which is partly regulated by the level of GOAT, may
affect energy metabolism and feeding.
Ghrelin plasma levels increase prior to a meal to induce hunger and decrease
rapidly at the end of a meal, indicating satiety (Mishra et al. 2016). Ghrelin induces
food intake centrally via neurons of the ARC, specifically through activation of
neuropeptide Y (NPY) and agouti related peptide (AgRP) neurons (Sato et al.
2005; Ferrini et al. 2009). Plasma ghrelin levels are positively correlated with body
mass index (BMI), except in obese individuals which have paradoxically low levels
of ghrelin (Tschöp et al. 2001). However, the decrease in total plasma ghrelin in
obesity has been attributed to a decrease in circulating UAG concentrations,
whereas AG concentrations remain at a similar level (Barazzoni et al. 2007;
Pacifico et al. 2009). It is hypothesised that UAG is more quickly degraded in obese
individuals, possibly due to increased peptidase activity (François et al. 2015).
Despite the lower circulating total ghrelin levels in obesity, it is hypothesised that
a greater threshold must be reached in obese individuals in order to suppress the
orexigenic signalling of ghrelin and induce satiety (Roux et al. 2009). Therefore,
obese individuals may continually have an increased appetite which is more
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difficult to satisfy. This is supported by evidence which suggests that obese
individuals need to consume a greater number of calories in order to suppress
ghrelin levels compared to non-obese individuals (Roux et al. 2009).
Ghrelin O-acyltransferase (GOAT)
GOAT is expressed at higher levels in the stomach, the major site of ghrelin
acylation, and is co-expressed with ghrelin in the pancreas (Gutierrez et al. 2008).
GOAT is not only expressed in gastric mucosal cells, but has also been found to
circulate in the plasma (Goebel-Stengel et al. 2013). Plasma levels of GOAT are
increased in obese individuals compared to healthy weight individuals. In fact
there is a positive correlation between circulating levels of GOAT and BMI, while
GOAT has a negative correlation with ghrelin in obese individuals. This suggests
GOAT may have a role in long term energy metabolism, possibly influencing the
development or state of obesity (Goebel-Stengel et al. 2013).
GOAT is regulated by a number of growth factors and hormones, including growth
hormone releasing hormone (GHRH), leptin, somatostatin and AG itself, however
not UAG (Gahete et al. 2010). Interestingly, AG may be able to influence its own
production by stimulating the expression of GOAT. Gahete and colleagues (2010)
found that total ghrelin levels were decreased, with no change in AG levels, in
diet-induced obese mice. This was accompanied by reduced total ghrelin levels in
the stomach but no change in GOAT mRNA expression. It should be noted that
this study did not report the expression of GOAT protein. Therefore, there may be
additional factors which influence circulating AG levels, such as the rate of AG
degradation or GOAT enzyme and/or UAG levels (Gahete et al. 2010).
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Serotonin 2C Receptor (5-HT2CR)
5-HT is also involved in appetite and food incentive, and consequently, weight
regulation. 5-HT is largely known for its psychological effects that are elicited via
binding to one of a large family of receptors categorised into subtypes. It is
through the serotonin 2C receptor (5-HT2cR) that 5-HT induces satiety (Tecott et
al. 1995; Werry et al. 2008) via the central melanocortin system (Garfield et al.
2016) which makes 5-HT2cR a potential target for controlling obesity. 5-HT2CR is
involved in the regulation of appetite and food intake through homeostatic feeding
mechanisms in the hypothalamus along with reward and food incentive in the
ventral tegmental area (VTA) (Garfield et al. 2016; Valencia-Torres et al. 2016).
5-HT2cR is one of a family of seven transmembrane domain receptors which
produce inter-cellular signals through G-proteins (Werry et al. 2008). Experiments
by Tecott et al. (1995) and Nonogaki et al. (2002) illustrate the role of 5-HT2cR in
appetite regulation, through the use of mice lacking functional 5-HT2cR which
resulted in obesity induced by hyperphagia (excessive eating). Other research has
shown that 5-HT2cR can form heterodimers with the GHSR-1a in the brain
suggesting that there could be a link between the ghrelin axis and serotonin
pathways (Schellekens et al. 2013). A recent study investigated the role of GHSR
in food intake, particularly focusing on the role of central GHSR in food intake in
a mouse model. Neuronal deletion of GHSR almost completely prevented diet-
induced obesity (Lee et al. 2016). This suggests that central GHSR, most likely
due to activation by ghrelin, affects energy metabolism and may be a potential
anti-obesity target (Lee et al. 2016).
Two populations of neurons are located in the ARC of the hypothalamus which
exhibit opposite effects on feeding and energy metabolism. POMC neurons express
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α-melanocyte stimulating hormone (α-MSH) while the other neurons express AgRP
(Heisler et al. 2002). Both α-MSH and AgRP act on the melanocortin 4 receptor
(MC4R), with agonistic and antagonistic abilities to illicit an anorexigenic or
orexigenic response respectively (Kawahara et al. 2008; Heisler et al. 2002). 5-
HT2CR is expressed by, and regulates the activation of, ARC POMC neurons (Heisler
et al. 2002). 5-HT acts on the MC4R pathway, by binding to 5-HT2CR on POMC
neurons which act on α-MSH upstream of MC4R to produce an anorexigenic effect,
therefore inducing satiety (Kawahara et al. 2008; Berglund et al. 2013).
Serotonin agonists in the treatment of obesity
Both circulating 5-HT levels in the periphery, and central 5-HT levels in the brain,
decrease in response to high-fat diet induced obesity in animal models (Kim et al.
2013; Zemdegs et al. 2016) with a negative correlation shown between 5-HT
levels and weight gain (Kim et al. 2013). A study by Derkach et al. (2015)
demonstrated that long-term intranasal 5-HT treatment of a high fat diet and low
dose streptozotocin-induced diabetic rat model led to improved metabolic
parameters with a decrease in body weight and food intake compared to the
diabetic group without 5-HT treatment (Derkach et al. 2015). This supports the
role of 5-HT in metabolism and appetite and food intake regulation.
With the increasing obesity pandemic, 5-HT2CR gained interest as a potential
target for reducing obesity. Put simply obesity occurs due to a surplus of energy
compared to energy expenditure. Thus diet and physical activity are seen as the
two most important factors in energy regulation. Considering the role of 5-HT2CR
in appetite regulation and satiety, a selective 5-HT2CR agonist may be an effective
therapeutic approach against obesity. D-fenfluramine, an indirect 5-HT agonist,
was marketed as an effective weight-loss drug (Heisler et al. 2002). Due to the
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lack of selectivity for specific 5-HT receptors, cardiovascular complications
occurred in some patients and the drug was withdrawn from use (Heisler et al.
2002). A selective 5-HT2CR agonist, Lorcaserin hydrochloride, was approved for
use as an adjunct therapy to a reduced-calorie diet and increased physical activity
for chronic weight management for obese or overweight individuals with at least
one weight-related comorbidity (Boge et al. 2014). A recent study by Valencia et
al. (2016) showed that neurons in the VTA which express 5-HT2CR further
modulate food intake by influencing incentive and motivation behaviours. It was
shown that chemogenic activation of VTA 5-HT2CRs in rats significantly reduced ad
libitum food intake by 59%, which was comparable to the 60% reduction of food
intake achieved by administration of Lorcaserin.
Expression of 5-HT2CR in the brain in response to diet
It is known that plasma 5-HT levels are decreased in animal diet-induced obesity
models due to a high fat diet. However, it is unknown whether a HCHF diet,
representative of the Western diet, leads to changes in the expression of 5-HT2CR
in the brain thereby influencing the brain’s response to 5-HT.
Lopez-Esparza et al. (2015) investigated the effect of the addition of tryptophan
supplementation to a high energy diet, on the expression of the serotonin
receptors 5-HT2CR and 5-HT2AR in the rodent brain. The amino acid L-tryptophan
is of particular significance as it a precursor in the synthesis of 5-HT and it has
been shown that manipulation of plasma tryptophan levels via dietary
supplementation affects plasma 5-HT levels (van der Stelt et al. 2004). However,
it was unknown whether tryptophan levels also affected 5-HT receptor expression.
A diet-induced obesity (DIO) rodent model was used to compare the expression
of the serotonin receptors between control (CTR) rats fed a normal rodent chow
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diet, high energy diet (HED) (8% corn oil, 44% sweetened condensed milk and
48% purina rodent chow), control plus tryptophan (CTRW) or high energy plus
tryptophan (HEDW). Immunohistochemistry experiments showed a significant
difference in the expression of 5-HT2CR between CTR and HED rats, with HED
having decreased expression. Expression of 5-HT2CR was also decreased in the
HEDW compared to CTRW, however the reduction was not as great as seen
between the HED and CTR groups. Western blot analysis showed the HEDW had
the weakest expression of 5-HT2CR, however, the HEDW rats did not develop DIO.
As demonstrated by immunohistochemistry techniques, the expression of 5-HT2CR
was still reduced in the HEDW but potentially the addition of tryptophan prevented
the onset of DIO by increasing the synthesis and storage of 5-HT, therefore leading
to increased activation of 5-HT2CR (Lopez-Esparza et al. 2015).
Link between ghrelin axis and serotonergic pathway
Yamada et al. (2015) explored the link between stress and food intake in mice. In
aged male mice, exposure to a novel stressor resulted in a significant increase in
corticosterone and decreased food intake that was seen for 24 hours following
exposure. Aged female mice were not affected in the same way as male mice. This
is most likely due to the fact that the aged female mice had a higher basal level
of corticosterone and this level was not significantly affected by exposure to stress.
Plasma levels of AG significantly decreased in aged male mice following exposure
to the novel stressor, suggesting that decreased feeding is due to a stress-induced
decrease in AG. The decrease in AG was completely reversed by administration of
5-HT2CR agonist CP-809101 (3.0mg/kg). This not only supports the role of 5-HT2CR
in the regulation of food intake, but suggests that activation of 5-HT2CR may
decrease food intake through, at least in part, inhibition of AG release. Yamada et
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al. (2015) explored the role of oestrogen receptor α (ERα) on the food intake of
aged animals following exposure to a novel stressor. Administration of a low dose
of the ERα agonist propyl pyrazole triol (PPT) to aged male rats produced an
anorexigenic effect. This effect was decreased by administration of the 5-HT2CR
antagonist SB242084, suggesting that the anorexigenic effect of ERα is achieved
through an increase in 5-HT2CR activation. This is in agreeance with previous
studies which found that oestradiol increases 5-HT2CR protein synthesis in the
dorsal raphe region, caudal brainstem and hypothalamus (Henderson & Bethea
2008; Rivera et al. 2012; Santollo et al. 2012). The authors concluded that
exposure to a novel stressor results in ERα activation, leading to 5-HT2CR
hypersensitivity and ultimately activation of the hypothalamic-pituitary-adrenal
(HPA) axis and decreased food intake.
A study by Nonogaki et al. (2006) investigated the effect of feeding and fasting
on hypothalamic 5-HT2CR expression and plasma ghrelin levels in mice. 24 hours
fasting induced an increase in hypothalamic 5-HT2CR expression along with an
increase in circulating AG levels compared to the fed state. Treatment with 5-
HT2CR agonists m-chlorophenylpiperazine (mCPP) or fenfluramine significantly
reduced the increase in circulating AG levels seen with fasting and increased the
expression of hypothalamic POMC. These results support the notion of a negative
feedback mechanism between the central serotonergic pathway and ghrelin axis
in the regulation of energy homeostasis (Nonogaki et al. 2006). A study by
Schellekens et al (2013) further supports the link between the serotonin and
ghrelin pathways. This study provided evidence for a novel heterodimer between
GHSR1a and 5-HT2CR and that this dimerisation attenuates ghrelin-mediated
signalling through 5-HT2CR. Administration of RS102221, a specific 5-HT2CR
antagonist, restored GHSR1a mediated calcium signalling. This supports that 5-
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HT2CR can attenuate GHSR1a potentially through negative feedback upon
dimerisation (Schellekens et al. 2013).
The Gut Microbiome
Evidence is emerging to suggest that the composition of the gut microbiome can
have a profound effect on various physiological functions. Obese individuals
exhibit characteristic changes in their gut microbiome, with overall less bacterial
diversity and disrupted ratio of the two dominant bacterial phyla, Bacteroides and
Firmicutes (Mishra et al. 2016). Obese individuals characteristically have increased
numbers of Firmicutes and lowered numbers of Bacteroides in comparison to
healthy weight individuals. External factors can greatly influence the composition
of the gut microbiome. Diet is a significant determiner of the gut microbiome
composition, altering the residing microorganisms and the proportions in which
they are found. It has been suggested that the gut microbiome should be viewed
as an endocrine organ, due to the dynamic feedback which occurs between the
microflora and the host, and vice versa (Clarke et al. 2014). This concept is
supported by evidence which shows the plasticity and responsiveness of the gut
microbiome in response to dietary changes (Cotillard et al. 2013; O’Keefe et al.
2015; Salonen et al. 2014.
Studies in mice have shown greater microbial response to dietary changes, with
diet accounting for approximately 60% of variation in the gut microbiome,
compared to approximately 10% in humans (Faith et al. 2011; Salonen et al.
2014; Zhang et al. 2010). However, it should be noted that there is much less
inter-individual variation seen in the gut microbiome composition of laboratory
mice than humans. Walker et al. (2011) also demonstrated how rapidly the gut
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microbiome adjusts to dietary changes, with changes in the microflora evident in
around 3-4 days. However, these changes were reversed just as quickly.
Diet has also been shown to affect the cell biology of the colon. An innovative
study by O’Keefe and colleagues (2014) involved a two-week food exchange
between African American and African subjects, who generally consume a high-
fat, low-fibre Western style diet and high-fibre, low-fat African-style diet
respectively. Colonoscopy prior to exchange revealed adenomatous polyps in nine
African Americans (n=20), but no Africans (n=20). African Americans also had
significantly greater mucosal epithelial proliferation than the Africans. It has been
suggested that greater epithelial proliferation is an indicator of neoplasmic
(tumour-forming) change (O’Keefe et al. 2014). The risk of DNA mutations
occurring is increased due to a greater number of proliferating cells, which are
especially vulnerable to carcinogens and thus more susceptible to carcinogenesis.
It was suggested that the lower mucosal proliferation in Africans was associated
with greater butyrogenesis, with increased butyrate synthesising genes and higher
faecal butyrate concentrations also evident. Changes in the fibre and fat content
resulted in significant changes to the gut microbiome composition, with notable
changes in mucosal inflammation and proliferation. Following the dietary
intervention faecal butyrate concentrations increased on average by two and a
half times in the African Americans, while concentrations decreased by
approximately half in the Africans. Overall, the findings suggest that diet and the
gut microbiome are involved in colorectal carcinogenesis potentially through
epigenetic changes (modifications to DNA and chromatin without altering genetic
sequence) via butyrate (Paparo et al. 2014). Increasing fibre consumption may
offer a protective effect against colorectal cancer by increasing butyrogenesis
through modification of the gut microbiome.
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Short Chain Fatty Acids
Short chain fatty acids (SCFA) are the major metabolites produced from bacterial
fermentation of carbohydrate and protein in the GIT (Flint et al. 2015). Bacteria
in the GIT have direct access to nutrients and thus can alter host energy balance
by enhancing the calorie utilising capacity of the host. As such the production of
SCFAs is determined by host dietary intake, with SCFA production increasing with
greater intake of non-digestible carbohydrates, proteins and fats (Flint et al.
2015). It is estimated that more than 95% of SCFAs are absorbed by the colon
(Topping & Clifton 2001) with the major SCFAs, acetate, proprionate and butyrate
found at a molar ratio of approximately 60:20:20 (Cummings 1981).
Approximately 60-70% of the energy requirements of colonocytes (the epithelial
cells that line the colon) is acquired from fermentation products and butyrate is
the predominant energy substrate (Clarke et al. 2014; Topping & Clifton 2001).
The role of butyrate in intestinal health and epigenetics
Butyrate plays an important role in gut health and is integral to many areas
including: the maintenance of the intestinal barrier, regulation of intestinal motility
and visceral perception, immune regulation, ion absorption, amelioration of
mucosal inflammation and oxidation, and cell growth and differentiation (Canani
et al. 2011). Butyrate promotes colonocyte proliferation and cell differentiation in
the basal crypt, therefore decreasing the number and size of aberrant crypt focus
and reducing the risk of neoplastic lesions in the colon (Canani et al. 2011). As
butyrate is integral for maintaining colonocyte health, increasing the production
of butyrate could potentially protect against colorectal cancer. Not only is butyrate
an important energy source for colonocytes, but it has been demonstrated to have
anti-carcinogenic properties. Butyrate has opposing effects on the cell growth and
differentiation of healthy colonocytes compared to malignant cells (Canini et al.
Page 23 of 57
2011). This seemingly contradictory response is known as the ‘butyrate paradox’
(Canini et al. 2011). Butyrate can act as a histone deacetylase inhibitor (HDACi)
and may stimulate epigenetic changes, regulate gene expression and promote cell
cycle arrest, differentiation and/or apoptosis (Lazarova et al. 2004; Mátis et al.
2013). Butyrate influences inflammation and cell proliferation through regulation
of the NF-κB pathway, a key inflammatory pathway (Kumar et al. 2009).
Activation of the NF-κB pathway is regulated by the phosphorylation,
ubiquitination and degradation of its inhibitor IκB-α (Kumar et al. 2009). IκB-α is
ubiquitinated by E3-SCFβ-TrCP, a specific ubiquitin ligase complex (Kumar et al.
2009). It is through the ubiquitination and degradation of E3-SCFβ-TrCP that
butyrate attenuates activation of the NF-κB pathway (Kumar et al. 2009). Butyrate
can also hyperactivate the WNT/catenin signalling pathway (Lazarova et al. 2013)
with the butyrate-induced increase in WNT activity resulting in apoptosis in
colorectal cancer cell lines (Lazarova et al. 2004). Recently, Hu et al. (2015)
demonstrated another pathway through which butyrate inhibits colon cancer cell
proliferation and induces apoptosis. By down-regulating the proto-oncogene c-
Myc-induced expression of the oncogenic microRNA miR-17-92a, the expression
of miR-92a was also diminished (Hu et al. 2015). Furthermore, the addition of
exogenous miR-92a to colon cancer cells reversed the beneficial effect of butyrate
in inhibiting colon cancer cell proliferation.
Butyrate may also influence the gut microbiome composition through regulating
mucin secretion. A study by Jung et al. (2015) found that treatment of LS174T
human colorectal cells with butyrate resulted in a dose-dependent increase in
mucin protein. This decreased adherence of the bacteria Escherichia coli, while
increasing adherence of more beneficial Lactobacillus and Bifidobacterium
Page 24 of 57
bacterial strains. Thus, butyrate also maintains the health of colonocytes through
modulation of the mucosal layer.
One approach to increasing butyrate production is via dietary changes; by
increasing the intake of foods which are metabolised to produce butyrate. All non-
digestible carbohydrates and unabsorbed monosaccharides which reach the large
intestine can theoretically produce butyrate through their fermentation (Morrison
et al. 2006) however, there are some particular groups which have a greater
butyrogenic capacity, such as RS and oligofructose (OF) (Klessen et al. 2001). It
has been reported that OF compounds, in particular inulin- type fructans, increase
the production of butyrate and also increase the numbers of Bifidobacteria spp.,
which are thought to be particularly beneficial to the host. Given that inulin-type
fructans promote both a butyrogenic and bifidogenic effect, it is hypothesised that
there is a relationship between Bifidobacterium and butyrate production.
Bifidobacterium do have the ability to metabolise inulin-type fructans, and in fact,
have been reported to have a preference for OF. However, Bifidobacterium do not
produce butyrate (De Vuyst & Leroy 2011). It is believed that the butyrogenic
characteristic of Bifidobacterium is due to cross-feeding with other
microorganisms (De Vuyst & Leroy 2011). It is hypothesised that the metabolic
products of Bifidobacterium may be utilised by butyrate producing bacteria,
resulting in an overall increase in butyrogenesis (Belenguer et al. 2006).
Belenguer et al. (2006) investigated the possibility of a metabolic cross-feeding
mechanism between lactate-producing Bifidobacterium adolescentis and butyrate-
producing Eucbacterium hallii and Anaerostipes caccae, two members of the
Firmicutes phyla. Co-culture of E. hallii and B. Adolescentis on starch resulted in
butyrogenesis, which did not occur when each bacterial species were grown
Page 25 of 57
separately in pure culture (Belenguer et al. 2006). Investigations of the carbon
flow between the two bacterial species confirmed that the fermentation of starch
by B. Adolescentis produces lactate which is utilised by E. hallii to produce butyrate
(Belenguer et al. 2006). Similar findings were evident when B. Adolescentis was
co-cultured with A.caccae. Microorganisms in the Firmicutes phyla are generally
good producers of butyrate (Belenguer et al. 2006). Thus it may seem
counterintuitive that Firmicutes numbers are increased in obese individuals
compared to lean individuals given that obesity is a risk factor for colon cancer,
and the important role that butyrate plays in maintaining colonocyte health.
However, it is hypothesised that due to the metabolic cross-feeding relationship
Firmicutes has shown with Bifidobacteria, the butyrogenic characteristic of
Firmicutes may be reliant on the presence of other microorganisms such as
Bifidobacteria. Unpublished data has shown that during the gut microbiome
characterisation, the Bifidiobacterium were completely removed by the feeding of
HCHF diet against a 14% population in the CS diet in Wistar rats (unpublished
data from USQ Functional Foods Research Group – Panchal et al.). This suggests
that diet-induced obesity may deplete Bifidobacterium spp., consequently causing
a decrease in butyrate production and increased risk of cancer potentially through
epigenetic changes. Therefore measures which increase Bifidobacterium such as
low fat and low carbohydrate diet or through probiotic (with Bifidobacteria spp.)
and prebiotic supplementation, offer a potential mechanism of increasing butyrate
production and ultimately reducing the risk of carcinogenesis.
Page 26 of 57
Hypotheses
The hypotheses of this study were that:
1. The HCHF diet would lead to a decrease in the expression of the satiety signal
5-HT2CR and an increase in the expression of the ghrelin appetite signals in
comparison to the CS diet;
2. The H8C8 diet would change the gene expression of the HCHF diet back to the
expression of the CS diet rats;
3. The microbiome in the HCHF diet rats would induce gene expression changes
in chromatin modifying enzymes in colon cells that were different to those induced
by the microbiome of CS diet rats.
Aims and objectives
The objective of this study was to use a male Wistar diet-induced obese rat model
to investigate the effect of a HCHF diet on the gene and protein expression
patterns of ghrelin, GOAT, GHSR and 5-HT2CR in the brain.
The aims were to:
1. Measure the mRNA gene expression of ghrelin, GOAT GHSR and 5-HT2CR in
the brain tissue of rats fed a control diet based on CS or treatment diets of
either 16 weeks of HCHF or eight weeks of HCHF followed by eight weeks
of the CS diet.
2. Determine whether any changes in gene expression were also evident at
the protein level.
3. Investigate whether the gut microbiome from rats fed a HCHF diet could
stimulate epigenetic changes in colon cells by stimulating the gene
expression levels of chromatin modifying enzymes.
Page 27 of 57
CHAPTER 2
EXPERIMENTAL PROCEDURES
Tissue collection
Male Wistar rats were fed either a corn starch (CS) (n=3), high carbohydrate and
high fat (HCHF) diet (n=4), a high carbohydrate and high fat for eight weeks then
corn starch for eight weeks (H8C8) (n=4) or modified HCHF (n=3) or CS (n=3)
diets (Refer to Appendix A for detailed descriptions of diet). Collection of brain
tissue samples was performed during the scheduled termination for each rat
following 16 weeks on the diets. Tissue collection was mostly outsourced, being
completed by other individuals. Tissue samples were collected directly following
sacrifice and placed on disposable weigh boats on ice. Bench space, mortar and
pestles and spatulas were RNase-zapped to reduce RNA degradation. This was
done at the beginning of experimentation and then in between the use of the
mortar and pestle for each different tissue sample. Samples were snap-frozen in
liquid nitrogen and homogenised to a fine powder using liquid nitrogen and a
mortar and pestle. For each RNA sample, 600µl of RLT buffer (containing 1% β
mercapto-ethanol) was added. A 5 gauge syringe and needle was then used to
further homogenise each sample into solution. All samples were then stored at -
80˚C until use.
Protein extraction
Brain tissue samples were weighed to be approximately 0.075g per 500µl
radioimmunoprecipitation assay (RIPA) buffer with protease and phosphatase
inhibitors added. Tissue samples were homogenised in RIPA buffer using a 3mL
syringe and 19 gauge needle. The lysates were then placed in a test-tube rack in
an esky with ice and water to achieve a 4°C environment, on a plate shaker for
Page 28 of 57
two hours. Samples were then centrifuged for 20 minutes at 12 000 rpm at 4°C.
The supernatant was then carefully removed and placed in a microfuge tube, the
pellet was discarded. The extracted protein was then aliquoted into 100µl and 25µl
aliquots and stored at -80°C. A bicinchonic acid (BCA) assay was performed on
the protein extracts to determine concentrations.
mRNA extraction
30mg of brain tissue (animals: CS1, CS2, CS3, HCHF1, HCHF2, HCHF3, HCHF4,
H8C81, H8C82, H8C83, H8C84) was weighed and placed in a microfuge tube.
Favorgen RNA extraction kit was used to perform RNA extractions (FavorPrep
Tissue Total RNA Mini Kit 2009). 350µl of FARB Buffer and 3.5µl of β mercapto-
ethanol was added to the microfuge tube. The tissue samples were homogenised
by passing the lysate through a 25 gauge needle syringe 10 times. The
homogenised sample was then transferred to a filter column in a collection tube,
then centrifuged for two minutes at 18000 x g. The clarified supernatant was
transferred from the collection tube to a new microfuge tube. One volume of 70%
RNase-free ethanol was added to the microfuge and mixed by vortex. The sample
mixture was then added to a FARB Mini Column in a collection tube and centrifuged
for one minute at 18000 x g. The flow through was discarded and FARB Mini
Column returned to the collection tube. 500µl of Wash Buffer 1 was added to the
FARB Mini Column and centrifuged at 18000 x g for one minute. Flow through
discarded. 750µl of Wash Buffer 2 was added to the FARB Mini Column and
centrifuged for one minute at 18 000 x g. This step was repeated with another
750µl of Wash Buffer 2. The FARB Mini Column was the centrifuged for another
three minutes to dry the column. The FARB Mini Column was placed in an elution
tube and 40µl of RNase-free double-distilled water added. The FARB Mini Column
Page 29 of 57
was allowed to stand for one minute before centrifuging for one minute at 18 000
x g to elute the RNA.
cDNA synthesis
Following quantification by the NanoDrop (Implen), the samples used for mRNA
extraction were converted to cDNA by using a BIO-RAD Reverse Transcription Kit
(iScript cDNA Synthesis Kit 2017). A master mix was made for each sample with
a one volume reaction made with 4µl 5 x iScript Reaction Mix, 1µl iScript Reverse
Transcriptase with appropriate amounts of RNA and RNase-free H2O.
Analysis of gene expression by real-time quantitative polymerase
chain reaction
Preliminary experiments investigated the gene expression of various targets
including ghrelin (GHRL), growth hormone secretagogue receptor (GHSR),
ghrelin-o-acetyltransferase (GOAT), mucin 2 (MUC2), serotonin 2C receptor (5-
HT2CR), tryptophan 5-hydroxylase 1 (Tph1) and toll-like receptor 4 precursor
(Tlr4). Based on the findings from the preliminary screening, further experiments
were conducted investigating the gene expression of GHRL, GHSR, GOAT and 5-
HT2CR, specifically focusing on the effect of a HCHF diet on the ghrelin and 5-HT
pathways in the gut-brain axis. Brain tissue samples were obtained from male
Wistar rats representing three different dietary conditions: CS (n=3), HCHF (n=4)
and H8C8 (n=4). The expression of the genes of interest were analysed by RT-
PCR. RT-PCR was performed using validated PrimePCR primers (BIO-RAD
Laboratories Inc., USA). Analysis of gene expression was achieved using the 2-ΔΔCT
method, giving the fold change in gene expression due to the treatment diet
compared to the normal diet, normalising to polyubiquitin-C precursor (UBC) as a
stable reference/housekeeping gene (Silver et al. 2008). As seen below, firstly
ΔΔCT is calculated by subtracting ΔCTC from ΔCTE. ΔCTE is the difference between
Page 30 of 57
the average cycle threshold for the gene target (i.e. ghrelin, GOAT, etc) and the
reference/ housekeeping gene (Ubiquitin C) using cDNA from the treatment diet
(experimental) rats. While ΔCTC is the difference between the average cycle
threshold for the gene target (i.e. ghrelin, GOAT, etc) and the reference/
housekeeping gene (Ubiquitin C) using cDNA from the normal diet rats.
ΔCTE-ΔCTC=ΔΔCT
2-ΔΔCt= Fold change in expression compared to control diet
Western Blot (Immunoblots)
Protein lysates from brain tissue of rats fed CS (n=2) (animals 1 and 3), HCHF
(n=2) (animals 3 and 4), H8C8 (n=2) (animals 1 and 3) and pooled samples from
modified corn starch (n=3) (mCS) and modified high fat high carbohydrate (n=3)
(mHCHF) fed rats were used to analyse 5-HT2cR protein expression. Protein lysates
were separated by denaturation on a SDS-PAGE on a 12% Amersham ECL Gel.
The proteins on the gel were electro transferred to nitrocellulose membrane by
using Life Technologies Mini Blot. The membrane was blocked with 10% skim-milk
powder diluted in Tris-buffered saline with Tween 20 (TBST) for one hour at room
temperature. The membrane was then incubated with mouse monoclonal IgG
antibody for 5-HT2CR (1:100, SR-2C (D-R): sc 17797, Santa Cruz Biotechnology,
USA) or β-actin (1:3000, BIO-RAD Laboratories Inc., USA) diluted in 5% blocking
buffer. The membrane was washed in TBST six times for five minute intervals. The
primary antibody was detected using goat-anti mouse horseradish peroxidase
(HRP) conjugate (1:1000, Santa Cruz Biotechnology, USA). The membrane was
incubated in the secondary antibody for one hour at room temperature. The
membrane was washed in TBST six times for five minute intervals. The
Page 31 of 57
immunocomplexes were visualised by enhanced chemiluminescence (ECL) by
combining 1mL each of Detection Reagent 1 Peroxide Solution and Detection
Reagent 2 Luminol Enhancer Solution (Thermo Fisher Scientific). The ECL solution
was mixed by inversion and poured onto cling film, then the membrane placed
protein side down on the solution, wrapped up in cling film then allowed to develop
for two minutes. Serial images were taken using a Fusion FX Vilber Lourmat
(Fisher Biotec) from one minute exposure, with the exposure time increasing 30
seconds between each image. Imaging continued until saturation was reached.
Co-culture of colon microbiome with human colon cancer cells
(SW620)
The co-culture protocol was adapted from the Human oxygen-Bacteria anaerobic
(HoxBan) coculturing system developed by Sadabad et al. (2015). Two pellets
were collected from the colon of the rats following termination, and immediately
placed in pre-prepared gifu anaerobe media (GAM). The cultures were placed in a
shaking incubator overnight at 37°C. Following 18 hours incubation, 500µl of colon
content culture inoculum was combined with 500µl of GAM agar mixture then
pipetted gently on top of pre-prepared semi-solidified GAM agar mixture in a falcon
tube. The falcon tube was then placed in an anaerobic culture chamber with
GENbox anaerobic sachet at 37°C for two and a half hours. The falcon tubes were
then removed and a scaffold with pre-cultured SW620 cells was added to the
falcon tube, along with fresh DMEM media to create an interface between the colon
content inoculum culture and the SW620 cells (Figure 2).
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Figure 2: Labelled photograph of the co-culture, illustrating the different sections of the
co-culture including the red scaffold with SW620 human colon cells.
The co-culture was then incubated at 37°C overnight. Scaffolds were then
removed and placed in 24 well plate and washed with trypsin to detach cells from
the scaffold. Cells were resuspended in phosphate-buffered saline (PBS) and
centrifuged to form a pellet. The remaining contents of the falcon tube was added
to a 50mL falcon tube with 25mL of PBS and centrifuged for five minutes at 4000
rpm to form a bacterial pellet. The pellet was then resuspended in PBS. (Refer to
Appendix B for detailed co-culture protocol).
Page 33 of 57
Epigenetic Chromatin Modification Enzyme Plate
RNA extraction was performed on the SW620 cell lysate as per Qiagen RNeasy
mini-prep kit instructions (RNeasy® Mini Handbook 2012). RNA was quantified
using the Nanodrop (Implen) and reverse transcription was performed using the
BIORAD iScript cDNA Synthesis kit to convert the RNA to cDNA as described
above. Master mixes were made for the pooled cDNA sample of the SW620 co-
culture lysate representing the modified corn starch (mCS) and modified high
carbohydrate high fat (mHCHF) diets. (Refer to Appendix A for detailed
comparison of diets). Samples and master mix were pipetted into each quadrant
of the epigenetic chromatin modification enzyme H384 plate (BIO-RAD
Laboratories Inc., USA) which RT-PCR used to measure the change in expression
of 86 genes associated with chromatin remodelling as well as five housekeeping
genes and five controls. ∆∆CT method was used to determine the fold change in
any targets that had a CT value of less than 35 as per the Minimum Information
for Publication of Quantitative Real-Time PCR Experiments (MIQE) Guidelines
(Bustin et al. 2009). Hypoxanthine phosphoribosyltransferase 1 (HPRT1) as a
reference gene.
Page 34 of 57
CHAPTER 3
RESULTS
Messenger RNA (mRNA) expression analysis by RT-PCR
Figure 3 demonstrates the pattern of expression exhibited in the HCHF and H8C8
diet group animals. For the HCHF diet, if ghrelin expression was increased in
comparison to rats fed a normal, corn-starch based diet (CS) as seen in animals
1 and 2, then GOAT and GHSR expression were also increased. Conversely, if
ghrelin expression was decreased compared to CS, as seen in animals 3 and 4,
GOAT and GHSR expression were also decreased. The effect of reverting back to
a CS diet for 8 weeks after consuming a HCHF diet for 8 weeks (H8C8) was also
not consistent for ghrelin expression amongst the rats. There was a consistent
and significant (p = 0.001) decrease in GOAT expression in all animals compared
to CS fed animals (Figure 4). All animals showed a decrease in GHSR expression
compared to CS fed rats. This decrease in GHSR expression in the H8C8 diet
compared to CS diet was statistically significant with a p value of 0.0153 (Figure
4). (Animal H8C83 was deemed an outlier for GHSR expression and excluded from
statistical calculations). There was no statistically significant mean change in gene
expression in ghrelin in the HCHF or H8C8 diet groups.
Page 35 of 57
A)
B)
C)
Figure 3: Illustrates the fold change of expression of A) ghrelin (GHRL), B) growth
hormone secretagogue receptor (GHSR) and C) ghrelin-O-acetyltransferase (GOAT)
compared to CS in each individual HCHF (1-4) and H8C8 animal (1-4). Standard error
values were calculated from at least three technical replicates within each individual
animal.
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
HCHF1 HCHF2 HCHF3 HCHF4 H8C81 H8C82 H8C83 H8C84
Fold
change c
om
pare
d t
o C
S
Animal ID
-16
-14
-12
-10
-8
-6
-4
-2
0
2
HCHF1 HCHF2 HCHF3 HCHF4 H8C81 H8C82 H8C83 H8C84
Fold
change c
om
pare
d t
o C
S
Animal ID
-5
-4
-3
-2
-1
0
1
2
HCHF1 HCHF2 HCHF3 HCHF4 H8C81 H8C82 H8C83 H8C84
Fold
change c
om
pare
d t
o C
S
Animal ID
Page 36 of 57
A)
Figure 4: Shows the mean A) Ghrelin, B) GOAT and C) GHSR expression change. A) One-
way ANOVA with post-hoc Tukey statistics showed no significant difference in ghrelin
expression in the HCHF or H8C8 diets. B) Statistics showed a significant (p= 0.001)
difference in the mean expression of GOAT compared to CS fed animals in H8C8 (n=4)
animals but not HCHF (n=4). C) Statistics showed a significant (p=0.0153) difference in
the mean GHSR expression in the H8C8 (n=3) animals, but not in HCHF (n=4) compared
to CS.
-1.4
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
HCHF H8C8
Fold
change c
om
pare
d t
o
CS
B)
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
HCHF H8C8
Fold
change c
om
pare
d t
o
CS
**
C)
-3
-2.5
-2
-1.5
-1
-0.5
0
HCHF H8C8
Fold
change c
om
pare
d t
o
CS
*
Page 37 of 57
Figure 5 shows the expression of 5-HT2CR was more consistent with all rats fed
the HCHF diet demonstrating a decrease in the expression of the 5-HT2CR and
three out of four rats demonstrating an increase in response to the H8C8 diet.
Figure 5: Fold change in 5-HT2cR expression in HCHF diet and H8C8 animals compared to
CS fed animals. Standard error values were calculated from at least three technical
replicates within each individual animal
Western (Immunoblot) Analysis of 5-HT2CR protein expression
Protein lysates from brain tissue of rats fed CS, HCHF, H8C8, mCS and mHCHF
were used to analyse 5-HT2cR expression. β-actin was used as a loading control
and was consistent between samples and the HeLa control lysate, however β-actin
signalling appeared at approximately 85 kDa (expected size is 42 kDa). Western
blot analysis showed no consistently significant difference in 5-HT2cR protein levels
between diet groups, indicated by varied the intensity of the bands (Figure 6).
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
1
1.5
HCHF1 HCHF2 HCHF3 HCHF4 H8C81 H8C82 H8C83 H8C84
Fold
change c
om
pare
d t
o C
S
Animal ID
Page 38 of 57
Figure 6: Illustrates the Western blot for 5-HT2CR expression using protein lysates from
CS (n=2), HCHF (n=2), H8C8 (n=2), modified CS (pooled samples n=3) and modified
HCHF (pooled samples n=3) animals. β-actin was used as a loading control.
Epigenetic chromatin modification enzyme H384 plate
There was a significant difference in the expression of the chromatin remodelling
enzyme DZIP3 (Deleted in azoospermia (DAZ) interacting zinc finger protein 3) in
the SW620 cell line in response to the mHCHF diet rat gut microbiome. The SW620
cell line co-culture exhibited a 12.55 fold increase in DZIP3 expression in mHCHF
compared to mCS samples, following use of the ΔΔCT method. This should be
further investigated as this target was considerably upregulated in response to
the high fat diet and DZIP3 is involved in chromatin remodelling, thus could lead
to epigenetic changes (Inoue et al. 2015).
Page 39 of 57
CHAPTER 4
DISCUSSION
This study supported a role for the ghrelin-serotonergic pathway in the brain in
response to a high fat and high carbohydrate diet. There was a significant change
in the brain expression of GHSR and GOAT between the H8C8 and CS groups
(Figure 4). There was also a trending decrease in expression of 5-HT2CR in
response to the HCHF diet compared to CS (Figure 5). This supports the
hypothesis that 5-HT2CR expression would be decreased in the HCHF group
compared to CS. Expression in the H8C8 group was comparable to CS, except for
animal H8C8 4 which appears to be an outlier in this case. This outlier is most
likely explained by variation during tissue sample collection. This supports the
hypothesis that converting back to a CS diet after eight weeks on a HCHF diet,
would return expression of genes involved in the ghrelin-serotonin axis to a level
comparable to CS fed animals. It was expected that there would be a significant
difference in the gene expression of the H8C8 diet compared to HCHF, as it was
hypothesised that eight weeks on the CS could reverse the effects of eight weeks
on the HCHF diet. It appears that the change in diet from HCHF to CS after eight
weeks on a HCHF diet is enough to reverse the trending decrease in 5-HT2CR that
was seen in the HCHF group. The decrease in 5-HT2CR in the HCHF group is
supported by the literature which gives evidence for the involvement of 5-HT2CR
in appetite and weight regulation and metabolism and suggests that diet may
affect the expression of brain 5-HT2CR (Garfield et al. 2016; Valencia-Torres et al.
2016). The decrease in 5-HT2CR expression in HCHF animals would decrease the
receptor availability for 5-HT binding and therefore attenuate the anorexigenic
pathway.
Page 40 of 57
There were differing patterns of mRNA expression in individual rats. For example,
in the HCHF diet, animals 1 and 2, expression of ghrelin, GOAT and GHSR
increased while the expression of 5-HT2CR decreased. This pattern of expression
is logical, and supports the hypothesis that the expression of the orexigenic ghrelin
axis would be increased in the HCHF diet, consequently resulting in an increase in
body weight (Appendix C). Furthermore, animals 1 and 2 have decreased
expression of 5-HT2CR, suggesting that the anorexigenic serotonergic pathway is
downregulated, which would further exacerbate the increase in bodyweight seen
with the HCHF diet. This also supports the hypothesis. Conversely, HCHF animals
3 and 4 had decreased expression of all target genes. This may be due to inter-
individual variation (Jasinska et al. 2009), however as the animals were all
littermates and genetically identical this is not likely. It is more likely that the
differences in trends between HCHF animals is due to variation in sample collection
from different regions of the brain. Further investigation is needed to fully
understand the role of the ghrelin-serotonin 2C receptor pathway in the brain in
appetite regulation and weight gain. As previously mentioned, plasma ghrelin and
GOAT levels increase with BMI (Goebel-Stengel et al. 2013). However, if GHSR
levels are decreased (as exhibited by HCHF animals 3 and 4), the orexigenic affect
will be attenuated due to decreased availability of GHSR. As the stomach is the
main site of synthesis of targets of the ghrelin axis and also 5-HT (Jenkins et al.
2016), it should be investigated whether similar expression changes are seen in
the stomach to those observed in the brain.
It is well documented that the level of gene expression of both ghrelin and 5-HT2CR
varies greatly between areas of the brain (Burns et al. 1997). The main source of
central ghrelin is the hypothalamus, however ghrelin expression has also been
reported at lower levels in the midbrain, hindbrain, hippocampus and spinal cord
Page 41 of 57
(Kojima et al. 1999; Ferrini et al. 2009). GHSR is also most highly expressed in
the hypothalamus (Wang et al. 2015). Ghrelin is also found in the pituitary where
it binds to GHSR to promote the release of growth hormone (Wang et al. 2015).
Ghrelin mRNA and protein expression is decreased in the hypothalamus after 24
and 48 hours fasting in rats (Sato et al. 2005). It is clear that the hypothalamus,
specifically the ARC, is integral in the regulation of food intake through the
expression of orexigenic and anorexigenic neurons, NPY and AgRP and POMC. It
is reasonable to expect that the hypothalamus would have greater expression of
genes related to appetite and metabolism, such as the ghrelin axis and
serotonergic genes. As previously mentioned, higher expression of these genes in
the hypothalamus and, also the pituitary as part of the growth hormone axis, is
well documented. It is possible, and likely, that the samples in this project were
collected from different areas within the brain. In order to improve the
experimental design and the integrity of the results it is recommended that a
conscious effort be made to collect tissue from the same region within the brain,
ideally the hypothalamus as it is a key location involved in the appetite regulation.
This is common practice within this area of research as demonstrated by Chiu et
al. (2014) and Garfield et al. (2016), who collected samples from the medial
prefrontal cortex and whole hypothalamus respectively. The use of microdissection
methods would increase the accuracy of sample collection. Additionally, the use
of immunohistochemical staining could be used to determine the location of gene
targets in a cross section of the brain. Neither of these techniques were a feasible
option for this project due to time and financial constraints. Alternatively, a punch
biopsy could be performed in order to compare the difference in expression of the
ghrelin axis and 5-HT2CR genes in various areas of the brain. This was not possible
Page 42 of 57
during this project due to time constraints and limitations on the availability of
tissue samples.
Additionally, it should be noted that due to the highly degradable nature of RNA it
is important that tissue collection be performed under optimal conditions to ensure
that a real representative of RNA and thus gene expression be achieved. This
includes using cleaning agents such as RN-ase Zap on all equipment (mortar and
pestle, microfuge tubes and other extraction equipment), changing gloves
frequently, working quickly as possible when handling samples and storing
samples at -80˚C.
Western blot analysis indicated that there was no significant difference in the
protein expression of 5-HT2CR between rats fed a CS, HCHF, H8C8, mCS or mHCHF
(Figure 6). While this does not consistently reflect the results of mRNA expression,
it should be noted that mRNA expression is not always an accurate representation
of the protein which is being translated. Pooled sampling of protein for mCS (n=3)
and mHCHF (n=3) does support the hypothesis. With less intense banding seen
for mHCHF compared to mCS, suggesting decreased expression of 5-HT2CR
protein. It is recommended that this experiment be repeated to conclusively
establish that there is no significant difference in 5-HT2CR protein expression due
to diet. A larger sample size within each diet group and consistent tissue sampling
from the same area of the brain would increase the integrity of the results.
Furthermore, additional quantification of the bands would enhance analysis of the
results.
Loading control was confirmed with consistent banding with a putative β-actin. β-
actin appeared at a molecular weight of approximately 85kDa, instead of 42kDa
which would usually be expected. Interestingly, the control lysate also appeared
Page 43 of 57
at this molecular weight. The blot was repeated with another β-actin antibody
from Santa Cruz, resulting in the same banding at around 85kDa. Other variables
such as primary and secondary antibody concentration were altered to confirm
that the unusual banding was not simply due to non-specific binding. Changing
these variables did not change the result, suggesting that the signal around 85kDa
is in fact some form of β-actin. This may be due to incomplete denaturation,
however standard protocol was followed, including the heating of samples and use
of β-mercaptoethanol (BME) in the loading buffer to denature the protein.
Furthermore, 5-HT2CR was successfully denatured as it appeared at the correct
molecular weight. Therefore, it is unlikely that the issue was incomplete
denaturation of protein. It is also unlikely that it was a problem with protein
migration through the gel, as previously stated, 5-HT2CR which is a similar
molecular weight (48kDa) to β-actin successfully migrated through the gel. It is
hypothesised that the larger molecular weight of β-actin is due to dimerisation
with another protein, however this has not been documented in the literature.
There was only one difference in the gene expression of colon cells in response to
the high fat diet which was DZIP3. DZIP3 is involved in epigenetic regulation via
its ubiquitination of HDACs (Inoue et al. 2015). It is hypothesised that diet-
induced changes in the microbiome resulted in a decrease in butyrate, a known
HDACi (Lazarova et al. 2004), through a decrease in Bifidobacterium. The
upregulation of DZIP3 expression by 12.55 fold in the HCHF assay was quite
considerable. DZIP3 ubiquitinates HDACs and butyrate inhibits HDACs. It is
possible that the increase in DZIP3 expression is the result of a compensatory
mechanism to account for the absence of butyrate due to changes in microbiome
composition as a result of HCHF diet. Potentially in the absence of butyrate, DZIP3
is involved in removing HDACs and therefore regulation of chromatin remodelling
Page 44 of 57
(Frank et al. 2016). Chromatin remodelling enzymes have an integral role in DNA
organisation and epigenetic modifications and include genes involved in post-
translational histone modifications (Marfella & Imbalzano 2007).
It would also be of interest to sequence samples from the rat gut microbiome
culture in order to compare the difference in microbiome composition of the rats
fed CS and HCHF diets or to perform qPCRs using primers specific to the 16s rDNA
of known butyrogenic bacteria. This would be advisable particularly as unpublished
data has shown that Bifidiobacterium were completely removed by the HCHF diet
against a 14% population in the CS diet in Wistar rats (unpublished data from
USQ Functional Foods Research Group – Panchal et al.). This is supported by
evidence from O’Keefe et al. (2014) who found a considerable increase in faecal
butyrate concentration due to diet changes. As previously mentioned,
Bifidiobacterium have butyregenic characteristics and butyrate is a known HDAC
inhibitor (HDACis) and may stimulate epigenetic changes, regulate gene
expression and promote cell cycle arrest, differentiation and/or apoptosis
(Lazarova et al. 2004). Due to time and financial constraints it was not possible
to establish the composition of the colon content culture microflora. It should also
be noted that the co-culture protocol used was novel in nature, thus there are
other factors, such as length of incubation that could be adjusted in order to
improve the experiment.
Conclusion
In conclusion, this study investigated the effects of diet and diet composition
change on the expression of the ghrelin and the serotonin receptor 5-HT2CR
pathway in the rat brain. The HCHF diet caused a trending decrease in the
expression of the 5-HT2CR and then a trending increase in response to the H8C8
Page 45 of 57
diet. The effect of reverting back to a CS diet for eight weeks after consuming a
HCHF diet for eight weeks (H8C8) led to a consistent and significant decrease in
expression of both GOAT and GHSR. Overall, these findings support the role of the
ghrelin-serotonin 2C pathway as a target for obesity. This is supported by the
emergence of 5-HT2CR agonists as adjunct therapy for obesity. These findings also
provided previously unreported evidence that targeting GOAT and/or GHSR along
with 5-HT2CR centrally in the brain may be a target for treating obesity and should
be further investigated.
Colon contents from rats fed on the HCHF and CS diets that were co-cultured with
human colon cells led to an increase in the expression of the chromatin modifying
enzyme DZIP3. This provided preliminary evidence of an epigenetic mechanism
whereby diet can influence the gut microbiome which can in turn alter the gene
expression of colon cells.
This study supports a role for diet composition in driving appetite regulation in the
brain through the expression of 5-HT2CR, GOAT and GHSR however this requires
further investigation. The use of microdissection to collect samples from different
parts of the brain involved in appetite regulation is recommended and may explain
inconsistent results. It is also recommended that Western immunoblot be
performed for both GHSR and GOAT to establish any changes in these genes at
the protein level. Future directions would be to investigate the use of small
molecule inhibitors of GOAT in reducing appetite and body weight in the obese rat
model (Garner & Janda 2011). This study also supports the further investigation
of the gut microbiome as a target for regulating the epigenome of colon cells.
Page 46 of 57
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APPENDIX
Appendix A
Modified corn starch and high carbohydrate, high fat diet break-down
Components
(g/kg)
mCS CS mHCHF HCHF
Corn starch (g) 570 570 - -
Fructose (g) - - 175 175
Condensed milk
(mL)
- - 395 395
Beef tallow (g) - - 150 200
Salt mixture (g) 25 25 25 25
Powered food (g) - 155 155
Skim milk powder
(g)
45 - 45 -
Vitamin mixture
from MP
Biomedicals (g)
5 - 5 -
Canola oil (mL) 5 - 5 -
Water (mL) 350 250 200 50
Drinking water
(mL)
No additives No
additives
25%
fructose
25%
fructose
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Appendix B
Gifu anaerobe media (GAM) preparation and rat colon content culture
1. Autoclaved GAM was retrieved from 4˚C overnight storage.
2. Aseptic technique was followed, working around a Bunsen burner. 1.5g
dextrose and 0.6g L-cysteine were dissolved in 50ml of distilled water. A filtered
syringe was used to add the dextrose and L-cysteine to the media, then pipetted
up and down.
3. A pH meter was used to measure the pH of the media, which was 5.8 at
first. NaOH was added until pH was 7.2.
4. 20ml of media was pipetted into 6 autoclaved McCartney jars, which were
then labelled (MCS28, MSC29, MCS30, MHCHF28, MCHF29, MCHF30).
5. During the tissue collection, approximately two pellets of colon contents
were placed into each appropriate jar of media, which was then incubated at 37˚C.
The terminations were staggered throughout the day, with MCS28 and MHCHF28
at approximately 8:30am, MCS29 and MHCHF29 at approximately 12:30pm and
MCS30 and MHCHF30 at approximately 3:30pm.
6. At approximately 7:00pm (10 hrs) all cultures were placed in a shaking
incubator at 150RPM and 37˚C, for overnight storage.
SW620 and colon content culture preparation
1. 1.5g of agar was added to 100ml of GAM (without dextrose and L-
cysteine) was autoclaved.
2. The autoclaved media was left for about 5min to cool before pipetting 6ml
of media into 8 labelled 10ml falcon tubes (MCS28, MCS29, MCS30, MHCHF28,
MCHF29, MHCHF30 and two controls) in a biosafety cabinet. The agar was left to
semi-solidify at room temperature for 30min. The remaining GAM agar was
placed on a heating block in order to remain molten.
3. The GAM and colon content cultures were retrieved from 37˚C incubation.
1ml from each culture was pipetted into 6 labelled 1.6ml cyrovials, then stored
at -80˚C.
4. 500µl of each rat colon content culture was added to labelled microfuge,
along with 500µl of molten GAM agar. This mixture was pipetted up and down
before transferring this to the corresponding falcon tube, pipetting very slowly in
order to preserve the integrity of the semi-solidified agar.
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5. The falcon tubes were placed in an anaerobic culture chamber with a
GENbox anaer sachet. The anaerobic culture chamber was placed in the
incubator at 37˚C for 2 ½ hours.
6. After 2 ½ hours the falcon tubes were removed from incubation. SW620
cell scaffolds were also removed from incubation.
7. 500µl of fresh DMEM media (without antibiotics or foetal calf serum) was
very slowly, drop by drop pipetted onto the GAM agar inoculum in one of the
control falcon tubes, to create an interfaced between the bacterial and cell
culture.
8. A SW620 inoculated scaffold was removed from the well containing foetal
calf serum, using two forceps (care was taken to only touch the outside of the
scaffold, not the cell-containing sides). The scaffold was then very carefully
placed onto the interface, with the most cell populated side facing down.
9. 500µl of DMEM media was the pipetted on top of the scaffold.
10. The lids of the co-cultures were then loosened, and the falcon tubes
incubated overnight 37˚C.
Tissue collection and sample homogenisation
1. Tissue samples were collected (see table) and homogenised. The
terminations were staggered throughout the day, with MCS28 and MHCHF28 at
approximately 8:30am, MCS29 and MHCHF29 at approximately 12:30pm and
MCS30 and MHCHF30 at approximately 3:30pm.
2. Tissue samples were collected directly following sacrifice and placed on
disposable weigh boats on ice.
3. Bench space, mortar and pestles and spatulas were RNase-zapped to
reduce RNA degradation originally then in between homogenisation of each
sample. Liquid nitrogen was used to cryogenically homogenised the tissue
samples with the mortar and pestle being used to grind to a fine powder. Some
tissues were easier to homogenise more finely than others. After
homogenisation, the spatula was used to divide the sample into two labelled
microfuge tubes, one for RNA and the other DNA, this was then placed in ice.
4. For each RNA sample, 600µl of RLT buffer (50% mercapto ethanol) was
added. A syringe and needle was then used to further homogenise each sample
into solution. Again, some tissues went into solution easier than others.
5. All samples were then stored at -80˚C.
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Appendix C
Animal weights
Rat Body weight (g) Total abdominal fat mass (g) *
Total abdominal fat mass (mg/mm)#
HCHF 1 553 46.76 954.31
HCHF 2 538 54.26 1064.00
HCHF 3 554 53.47 1091.22
HCHF 4 499 52.16 1043.10
Mean ± SEM 530 ± 12 51.13 ± 1.41 1030.51 ± 24.20
H8C8 1 438 20.42 416.69
H8C8 2 442 21.77 426.92
H8C8 3 432 29.98 611.84
H8C8 4 435 24.73 480.19
Mean ± SEM 437 ± 2 24.23 ± 2.12 483.91 ± 44.86
*The abdominal fat consists of retroperitoneal, omental and epididymal fat pads. #The fourth
column is abdominal fat (mg) normalised to tibial length (mm).
